Comparative Evaluation of Implant Planning Software

NCT06693635 | Completed

• 1 other identifier: AISoftware
• Study Type: observational
• Target: 1
• Locations: 1 country
• Sites: 1

Brief Summary

Artificial intelligence (AI) is increasingly being integrated into dental implant planning, revolutionizing the way clinicians approach treatment. AI-driven software can enhance the accuracy of implant placement by analyzing complex data sets, including bone density, anatomical structures, and patient-specific factors. This technology enables the creation of precise 3D models and surgical guides, facilitating more predictable and personalized treatment outcomes. Additionally, AI algorithms can automate tasks such as segmentation, matching digital impressions with CBCT scans, and even suggesting optimal implant positions. The integration of AI in implant planning not only improves clinical efficiency but also contributes to better patient outcomes by reducing surgical risks and enhancing the overall success of implant procedures.

Conditions

Edentulous Jaw; Edentulous Alveolar Ridge; Edentulous Mouth; Partial-edentulism

Keywords

Artificial Intelligence in Implantology; AI; Implant planning; AI software

Outcome Measures

Primary Outcomes (5)

• Segmentation of Bones

  The segmentation of bone structures and anatomical boundaries performed by the software will be evaluated.

  1 day

• Recognition of Neural structure

  The segmentation and recognition of nerve structures performed by the software will be evaluated.

  1 day

• Segmentation of teeth

  The segmentation of teeth performed by the software will be evaluated.

  1 day

• Bone density

  The bone hardness and density data will be evaluated at three different points. The value will be given on the Hounsfield Scale.

  1 day

• Time Workflow

  The execution time of each planning will be evaluated.

  1 day

Interventions

Implant planning DIAGNOSTIC_TEST

The implant planning will be carried out using various software programs. The AI assistance provided by each software will be evaluated.

Eligibility Criteria

• Age: 18 Years - 70 Years
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

All patients requiring implant rehabilitation with digital planning

You may qualify if:

• CBCT of Patient who needs Implant rehabilitations

You may not qualify if:

• Patient not suitable for implant rehabilitation

Sponsors & Collaborators

• University of Bari Aldo Moro: lead

Study Sites (1)

University of Bari Aldo Moro

Bari, 70124, Italy

Location

MeSH Terms

Conditions

Jaw, Edentulous; Mouth, Edentulous

Condition Hierarchy (Ancestors)

Jaw Diseases; Musculoskeletal Diseases; Stomatognathic Diseases; Mouth Diseases; Tooth Diseases

Study Officials

• Giuseppe D'Albis, Dr

  University of Bari Aldo Moro

  PRINCIPAL INVESTIGATOR

• Massimo Corsalini, Prof

  University of Bari Aldo Moro

  STUDY DIRECTOR

• Saverio Capodiferro, Prof

  University of Bari Aldo Moro

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: DDS, MSc

Study Record Dates

• First Submitted: November 14, 2024
• First Posted: November 18, 2024
• Study Start: November 1, 2024
• Primary Completion: November 1, 2024
• Study Completion: November 1, 2024
• Last Updated: January 1, 2025

Record last verified: 2024-12

Locations

IT (1)